An ultimate guide to Chatbot, its Development & Industry Applications

Chatbots, Python Development, Machine Learning, Natural Language Processing (NLP)

We (Humans) are constantly on the exploration mode looking out ways, which can simplify our lives and make it easier. And in that quest, we have come far from our preliminary stage.

From entering commands in an arcane language to fetch output to GUI to now we are developing bots that provides assistant to us by provide the freedom of entering any information. The Bots surrounding us today like Google Assistant, Apple Siri, Amazon Alexa are simplifying our life by automating mundane tasks, helping in our daily tasks and improving end-user experience. The demand of Chatbots has increased considerably and the predictions by Gartner are a testament to it

  • Over 50% Medium to large enterprises will have deployed product like chatbots in their services. [1]
  • Chatbots Market is expected to be worth 3.1 Billion USD by 2021 with a CAGR of 35% during 2016–2021. [2]
  • As per Juniper Research, the organizations will save up to $8 Billion in cost savings by 2021 with average time savings of 4 minutes per chat compared to traditional call centers. [3]

However, how does Chatbot work?

Chatbot is quite similar to a mobile Application. It has an application layer. API calls the server where it interacts with the database and gives back the answer. Conversational interface replaces user interface.

Chatbots work by extracting entities from the input by the end user, categorize it, cluster the information and map the relationship between the intent and the database to provide response.

It employs Intent Classification, Machine Learning Algorithms and Artificial Neural Networks into working.

Intent Classification

They classify the smallest unit of information i.e words into suitable categories and pulls back a response. Sometimes text classifier are also linked with external web reports to provide data to the user.

Example:

User: Who is Sachin Tendulkar?

Chatbot: Sachin Tendulkar is an Indian cricketer and the most number of run-scorers in International cricket.

Back-end processing: It assigned a category to the word “Sachin Tendulkar” and a response associated with the word was sent back to the user.

This technique works when the chatbot developer had specified Sachin Tendulkar with characteristics such as person, Indian cricketer, highest run scorer. Each such entities are trained so that it produces a correct response. However, this process is tedious and to reduce the work Ml algorithms are used.

Machine Learning Algorithms

Algorithms aids in processing of the input by the user. They adopt a reductionist approach to provide a more simplified solution to the above-mentioned structure. Words are counted for its occurrences and provided a score. Higher the score of a particular class or word the more likely it is the response with the input sentence. However, it does not guarantee if it is the perfect answer or not.

Artificial Neural Networks

Intelligent bots employ ANN into its working. They form a pattern during each conversation and learns from it. Words separated into different categories are fed as an input to the neural networks consisting of three inter-connected layers mainly input layer, hidden layers and output layer.

The bot maps relationship with each word (Class) and the most suitable response is given as an output to the user. The responses are saved and again trained with neural networks to learn more about the variations and prepare customized response.

It is necessary that the bots have been trained on different variations to avoid dead end that can frustrate the customer and hamper their experience over the platform.

How Chatbots are developed?

Chatbots are of two types mainly a Simple Question Answer based and an AI based conversationalist.

The Q/A based bot is hard-coded on the base of Manual Decision tree with limited functionality and capabilities. It works on the retrieval based model.

Examples:Wiki-Chatbot, Menu-based chatbot

Conversationalist bot also known as Dynamic bot or Intelligent bot works on Generative based model uses Natural Language Processing and deep learning to mimic the human based response. The bots learns from each conversations, it forms patterns, expands their variants and understands the nuances of different conversations and gives intelligent response to the user.

Examples: Siri, Alexa, Google Assistant.

Technology Stack behind the Bots

Bots are a mix of mobile and web- based and the technology stack depends on the application it is required. A combination of below mentioned stack is used for creating a chatbots

  • Scripts (Javascript, Ruby, PHP, Python, SQL, etc.)
  • JSON (JavaScript Object Notation) when specific data request are created by the browser example : Address of the store X This data format is structured and interchanged into text format by JSON and can be utilized by other programming languages. It basically improves the server to browser communications
  • A server to handle the API calls and HTTPS connections
  • Cloud service – It provides storage service (logs of each conversations) processing of the chats for better understanding of the intent and suitable response, Scalability.
  • NLP Framework – Intelligent bots make use of Machine Learning Algorithms and Natural language processing to have a deeper understanding of the syntax and semantics of the sentences.

Chatbot development platforms

Additionally Chatbot Development Platforms like Dialogflow, IBM Watson, Amazon Lex, Microsoft Bot Framework, Chatfuel, Manychat, wit.ai, Botsify, Flow XO, Beep Boop, Bottr, etc assist in creating basic chatbots without any need of technical knowledge. It consists of several functionalities which can be added via Graphical User Interface.

Chat/Conversation Platforms

In order to increase reach of the Chatbot and increase its effectiveness Chat Publishing Environment provides a perfect platform for the bots where user can interact with chatbot. Some of the such popular platforms are Google Assistant, Amazon Alexa, Facebook, Telegram, Skype, KIK, and many others.

Applications of Chatbot in different industries:

People today want on-time assistance, providing answers to their questions as they shoot. These has led to the rise in demand and need for organization to adopt a bot which can provide assistance and support whenever the end-user require.

Some of the areas where bots can be helpful are:

Specific Marketing: Organizations waste enough resources to divert the traffic to their website. The mantra to have a greater ROI of their investment has been simple to target the area where the customers are. With rise in the messaging platform such as Facebook Messenger, WhatsApp, KIK
Bots can leverage the reach of these platforms and spread awareness thereby reducing time, cost and effective coverage of their wide area

Customer Service Increased reach of the business leads to increased customer support for the end-user. Bots can be scaled as per requirement with little modifications it is possible to serve a large sector.

Healthcare: Personalized assistant to the patients, bridging the connection between the doctor and patients, Scheduling appointments and reminding patients for their routine check-up. Chatbot can also record health data, perform analytics which will help in decision-making. Examples: HealthVault, Izzy, Safedrugbot

E-commerce: How often it has been that customer after endless search has lost hope in finding the product that they are looking for. Bots trained with different characteristics of the product can act as a personal shop assistant and help them find the product that they are looking for.
This has dual advantage 1) Retaining the customer and increases customer satisfaction with on-time assistant. Example : TacoBot (Slack) & H&M (Kik)

Hospitality and Travel Agent: Hotel Industries can employ bots to update their inventories, process cancellation request and handle queries of the guest like availability of the rooms, room tariff. Bots when sufficient details provided to it can also prepare a complete travel itinerary and complete the process in quick time.

Fast Food chain: Bots via a conversational interface can convey varieties of the restaurant with pictures to the customers. Bots acting as a one-point contact can confirm the order, modify the order and receive payments. Automation of the complete process helps in speedy delivery and eliminates error in the complete process.

Stock Market Companies: Bots can learn from the history of different stocks, guide the users for the best possible investment option and help the users employ a effective investment plan without any hassle from the customers end. Bots can provide complete guidance of the stocks, update the value of the stocks and make/take payments on behalf of the customers.

Banking: 24*7* 365 banking services will be available to the customers. Freedom from manual KYC filling and auto-authorization of accounts. Besides assistance, chatbot also provides tools for analytics purpose that helps in targeting their service to the specific audience.


Chatbots are the next technological shift which every organizations is looking at and the advantages of it are clear visual indicator of its reach and effectiveness. If you are looking for more information or need guidance where chatbot can be helpful to you, feel free to drop us a message or an e-mail. We will be happy to guide you regarding the complete process.

 

References:

[1] https://www.gartner.com/smarterwithgartner/chatbots-will-appeal-to-modern-workers/
[2] https://www.marketsandmarkets.com/PressReleases/smart-advisor.asp
[3] https://www.juniperresearch.com/analystxpress/july-2017/chatbot-conversations-to-deliver-8bn-cost-saving

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